Deep Multi-Task Learning for Joint Estimation of Impulsive Noise Parameters

Keyphrases

• Impulsive Noise 100%
• Joint Estimation 100%
• Noise Parameters 100%
• Deep multi-task Learning 100%
• Multi-task Learning 50%
• Multi-task Learning Framework 50%
• Learning Model 25%
• Attention Mechanism 25%
• Learning Approaches 25%
• Wireless Systems 25%
• Representation Space 25%
• Wireless Communication Systems 25%
• CNN-LSTM Architecture 25%
• Accurate Estimation 25%
• Multiple Parameters 25%
• Fast Training 25%
• Statistical Parameters 25%
• Noise Parameter Estimation 25%
• Learning Efficiency 25%
• Weighted Loss Function 25%
• Learning Improvement 25%
• Stable Convergence 25%
• Memory Saving 25%
• Simultaneous Learning 25%
• Major Challenges 25%
• Computational Overhead 25%
• Effective Mitigation 25%
• Performance-complexity Tradeoff 25%
• Generalized Learning 25%
• Shared Representations 25%

Computer Science

• Multitask Learning 100%
• Learning Framework 50%
• Learning Approach 25%
• Experimental Result 25%
• Attention (Machine Learning) 25%
• Convolutional Neural Network 25%
• Long Short-Term Memory Network 25%
• Wireless System 25%
• Representation Space 25%
• wireless communication system 25%
• Fast Convergence 25%
• Parameter Estimation 25%
• Statistical Parameter 25%